Development and validation of an app-based cell counter for use in the clinical laboratory setting

Alexander C Thurman1, Jessica L Davis1, Max Jan2, Charles E McCulloch3, Benjamin D Buelow11 Department of Pathology and Laboratory Medicine, The University of California, San Francisco Medical Center, San Francisco, CA 94143-0102, USA2 Department of Pathology and Laboratory Medicine, The University of California, San Francisco School of Medicine, San Franacisco, CA 94117, USA3 Department of Epidemiology and Biostatistics, The University of California, San Francisco, San Francisco, CA 94107-1762, California, USA

Correspondence Address:
Alexander C ThurmanDepartment of Pathology and Laboratory Medicine, The University of California, San Francisco Medical Center, San Francisco, CA 94143-0102 USA

Source of Support: None, Conflict of Interest: None

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DOI: 10.4103/2153-3539.150252

Introduction: For decades cellular differentials have been generated exclusively on analog tabletop cell counters. With the advent of tablet computers, digital cell counters - in the form of mobile applications ("apps") - now represent an alternative to analog devices. However, app-based counters have not been widely adopted by clinical laboratories, perhaps owing to a presumed decrease in count accuracy related to the lack of tactile feedback inherent in a touchscreen interface. We herein provide the first systematic evidence that digital cell counters function similarly to standard tabletop units. Methods: We developed an app-based cell counter optimized for use in the clinical laboratory setting. Paired counts of 188 peripheral blood smears and 62 bone marrow aspirate smears were performed using our app-based counter and a standard analog device. Differences between paired data sets were analyzed using the correlation coefficient, Student's t-test for paired samples and Bland-Altman plots. Results: All counts showed excellent agreement across all users and touch screen devices. With the exception of peripheral blood basophils (r = 0.684), differentials generated for the measured cell categories within the paired data sets were highly correlated (all r ≥ 0.899). Results of paired t-tests did not reach statistical significance for any cell type (all P > 0.05), and Bland-Altman plots showed a narrow spread of the difference about the mean without evidence of significant outliers. Conclusions: Our analysis suggests that no systematic differences exist between cellular differentials obtained via app-based or tabletop counters and that agreement between these two methods is excellent.